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Public administration and services for citizens
08:18, 22 August 2025
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AI Factory Promises to Boost Efficiency in Russian Government Agencies

Russia has launched a centralized AI factory designed to speed up the deployment of artificial intelligence in government, cutting costs and improving services for citizens.

Government services get a digital upgrade

The new AI factory acts as a unified environment for developing and operating AI applications of any complexity. According to project developers, the technology can accelerate the adoption of AI in the public sector by a factor of ten, while cutting the cost of ownership for AI services by half. This means faster deployment of AI tools across government agencies, optimized budgets, and reduced workload for state authorities—key conditions for advancing digital governance.

For citizens, this will translate into quicker processing of requests, automated support from AI assistants, intelligent document analysis, and transparent monitoring of national projects. In practice, the initiative promises shorter service times, better quality of government work, and significant resource savings.

Security drives adoption

At this stage, the AI factory is primarily focused on domestic use. However, experts believe the platform could eventually attract international interest, particularly from countries seeking large-scale digital transformation of public services. To succeed globally, though, the initiative would require investment in adaptation and an export strategy.

When it comes to innovation, the financial side is crucial. Thanks to the unified AI factory ‘Cybox,’ which accelerates the development and deployment of AI solutions of any complexity for the public sector, it is now possible to cut AI costs by half and speed up implementation by up to ten times compared to standardized approaches. The ability to run as many as 200 AI projects simultaneously on one platform ensures effective scalability
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Within Russia, similar factories may soon appear across regions and government departments, and even at the municipal level. The platform supports up to 200 AI projects in parallel, making it possible to scale government digital initiatives in areas such as document flow automation, data analytics, monitoring of national programs, and deployment of AI assistants.

Security and ethics are integral to the platform’s design. Hardware-isolated environments ensure safe data processing, a critical factor for government applications.

From pilots to systemwide solutions

In recent years, demand for AI technologies in governance has surged. Until now, automation of citizen requests was tested only in separate agencies, without a centralized infrastructure. AI-based document analysis had also been limited, with efficiency hovering at around 40%. Monitoring of national projects relied on BI systems, which will now be complemented by AI analytics capable of revealing deeper links between indicators and events.

The launch of the AI factory marks a transition from scattered pilot projects to a comprehensive infrastructure—an important shift that signals a new level of coordination and oversight of AI initiatives in government.

Building scale and sustainability

The establishment of the AI factory is a strategic milestone in Russia’s digitalization push. It dramatically improves the balance of speed and cost in deploying AI solutions while introducing much-needed standardization and scalability. A single platform now makes it possible to unify and control AI processes across the public sector.

The infrastructure will continue to expand, supporting more projects and gaining new functionality. Over the next two to five years, the initiative is likely to spread geographically, including to municipal levels. Partnerships with tech companies could follow, enabling integration with commercial platforms. The model may also be adapted for international markets.

Still, the project faces risks that must be addressed to ensure long-term success. These include technical challenges (such as scaling under heavy loads), organizational hurdles (standardizing processes and training qualified personnel), and regulatory issues (ensuring data security and upholding ethical standards).

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